Senior Data Engineer job description
A Senior Data Engineer is a key role in technology and data-driven organizations, responsible for designing, building, and managing the infrastructure and tools that allow for the efficient processing and analysis of large data sets.
Use this Senior Data Engineer job description template to advertise open roles for your company. Be sure to modify requirements and duties based on the unique needs of the role you’re hiring for.
What is a Senior Data Engineer?
A Senior Data Engineer is a professional who specializes in preparing big data infrastructure for analytical or operational uses. They are responsible for designing and creating systems that collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret. Their work enables companies to make smarter decisions and optimize their operations.
What does a Senior Data Engineer do?
A Senior Data Engineer develops and maintains scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity. They collaborate with data scientists and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision making across the organization.
They play a crucial role in implementing software and methodologies for data correction, reconciliation, and quality checking.
Responsibilities of a Senior Data Engineer include:
- Designing and implementing ETL processes
- Managing data warehousing solutions
- Exposing and deploying machine learning models to production
- Ensuring data quality and consistency across various sources
Job brief
We’re seeking a Senior Data Engineer to enhance our Data Science Team, focusing on implementing and managing data workflows that support machine learning models and large-scale analytics. This role involves designing ETL processes, ensuring data quality, and deploying ML models to production.
The ideal candidate will have a strong computer science background, advanced Python knowledge, and experience with cloud services, SQL/NoSQL databases, and Docker/Kubernetes.
You’ll work closely with our data science and product teams to drive insights and innovations.
Responsibilities
- Design and implement ETL processes for data transformation and preparation
- Deploy machine learning models to production environments
- Manage data pipelines for analytics and operational use
- Ensure data accuracy and integrity across multiple sources and systems
- Collaborate with data scientists to support NLP algorithms and analytics
Requirements and skills
- 4+ years of experience in data engineering within a production environment
- Advanced knowledge of Python and Linux shell scripting
- Experience with SQL/NoSQL databases (e.g., Redshift, Postgres, MongoDB)
- Proficiency in building stream processing systems using Kafka
- Familiarity with Docker, Kubernetes, and cloud services (AWS, GCP)
- Bonus: Experience with the ELK stack and machine learning knowledge
Frequently asked questions
- What does a Senior Data Engineer do?
- A Senior Data Engineer designs, builds, and maintains the infrastructure and tools needed to handle large datasets. They develop ETL processes, ensure data quality, and deploy machine learning models to production, supporting data-driven decision-making.
- What are the duties and responsibilities of a Senior Data Engineer?
- Their main duties include managing data pipelines, ensuring data integrity, deploying ML models, and collaborating with data scientists and analysts. They also work on stream processing and data warehousing solutions to support analytics and operational needs.
- What makes a good Senior Data Engineer?
- A good Senior Data Engineer has a strong foundation in computer science, expertise in data management technologies, and experience with cloud services. They are problem solvers, capable of designing scalable data systems and ensuring data quality and consistency.
- Who does a Senior Data Engineer work with?
- They work closely with data scientists, analysts, product managers, and IT teams to provide the data infrastructure necessary for analysis and operational use. Collaboration with stakeholders across the organization is key to align data engineering efforts with business objectives.
- How important is a Senior Data Engineer in a data-driven organization?
- In a data-driven organization, a Senior Data Engineer is crucial for building and maintaining the backbone of data systems. Their work enables the organization to leverage big data for insights, optimizations, and innovations, making them central to achieving strategic goals.